---
license: apache-2.0
base_model: jbomdev/AlterEgo
language:
- en
pipeline_tag: text-generation
library_name: transformers
tags:
- gguf
- llama.cpp
- ollama
- text-generation
- from-scratch
- chatml
---

<div align="center">

# 🧠 AlterEgo-373M - GGUF

**GGUF builds of a 373M language model designed, trained, and served entirely from scratch.**

[![Model](https://img.shields.io/badge/🤗-Original%20model-yellow)](https://huggingface.co/jbomdev/AlterEgo)
[![Code](https://img.shields.io/badge/GitHub-AlterEgo%20(training)-181717?logo=github)](https://github.com/J-bom/AlterEgo)
[![Platform](https://img.shields.io/badge/GitHub-LLME%20(platform)-181717?logo=github)](https://github.com/J-bom/LLME)
[![Params](https://img.shields.io/badge/params-373M-green)]()

</div>

---

GGUF quantizations of [**jbomdev/AlterEgo**](https://huggingface.co/jbomdev/AlterEgo), a 373M-parameter decoder-only model built from the ground up: architecture, training, tokenizer, and inference all written from scratch. For the full story, including architecture, training curves, hyperparameters, and benchmarks, see the [main model card](https://huggingface.co/jbomdev/AlterEgo).

## Run it with Ollama (one command)

```bash
ollama run hf.co/jbomdev/AlterEgo-GGUF:Q8_0
```

Swap the tag for any quant in the table (`:Q4_K_M`, `:F16`). The ChatML template, stop tokens, and sampling defaults are applied automatically from the GGUF metadata and the `params` file in this repo.

## Run it with llama.cpp

```bash
llama-cli -hf jbomdev/AlterEgo-GGUF:Q8_0 -p "Tell me about the ocean."
```

## Quantizations

| File | Quant | Size | Notes |
|---|---|---|---|
| `alterego-Q8_0.gguf` | Q8_0 | ~0.4 GB | **Recommended.** Near-lossless, still tiny. |
| `alterego-Q4_K_M.gguf` | Q4_K_M | ~0.25 GB | Smallest. Some quality loss, more noticeable on a model this small. |
| `alterego-F16.gguf` | F16 | ~0.75 GB | Full precision, max quality. |

AlterEgo is small enough that Q8_0 (or even F16) runs comfortably on any laptop, and at this scale those preserve quality better than aggressive 4-bit quantization. Reach for Q4_K_M only if you want the smallest possible download.

## Recommended generation settings

These are the defaults AlterEgo was tuned and served with in LLME:

| Parameter | Value |
|---|---|
| `temperature` | 0.7 |
| `top_k` | 50 |
| `top_p` | 1.0 |
| `repeat_penalty` | 1.1 |

## Chat format

AlterEgo uses **ChatML**, and stops on `<|im_end|>` or `<|endoftext|>`:

```
<|im_start|>system
{system prompt}<|im_end|>
<|im_start|>user
{message}<|im_end|>
<|im_start|>assistant
```

## Limitations

A 373M model on a modest token budget behaves like one: it can be factually wrong, repeat itself, and lose coherence on long prompts. English only. Not safety- or preference-tuned. See the [main model card](https://huggingface.co/jbomdev/AlterEgo#limitations) for details.

## License

Apache 2.0, same as the [base model](https://huggingface.co/jbomdev/AlterEgo).